{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "view-in-github"
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/jermwatt/machine_learning_refined/blob/main/notes/6_Linear_twoclass_classification/6_4_Perceptron.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "RtQPeQK5nnEG"
   },
   "source": [
    "## Chapter 6: Linear two-class classification"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook contains interactive content from an early draft of the university textbook <a href=\"https://github.com/neonwatty/machine-learning-refined/tree/main\">\n",
    "Machine Learning Refined (2nd edition) </a>.\n",
    "\n",
    "The final draft significantly expands on this content and is available for <a href=\"https://github.com/neonwatty/machine-learning-refined/tree/main/chapter_pdfs\"> download as a PDF here</a>."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tXFjXqvVnnEI"
   },
   "source": [
    "# 6.4 The Perceptron"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "-tk8DDs3nnEI"
   },
   "source": [
    "As we have seen with logistic regression we treat classification as a particular form of nonlinear regression (employing - with the choice of label values $y_p \\in \\left\\{-1,+1\\right\\}$ - a tanh nonlinearity).  This results in the learning of a proper nonlinear regressor, and a corresponding *linear decision boundary* \n",
    "\n",
    "\\begin{equation}\n",
    "\\mathring{\\mathbf{x}}_{\\,}^{T}\\mathbf{w}^{\\,}=0.\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ri75a3HfnnEI"
   },
   "source": [
    "Instead of learning this decision boundary as a result of a nonlinear regression, the *perceptron* derivation described in this Section aims at determining this ideal lineary decision boundary directly.  While we will see how this direct approach leads back to the *Softmax cost function*, and that practically speaking the perceptron and logistic regression *often results in learning the same linear decision boundary*, the perceptron's focus on learning the decision boundary directly provides a valuable new perspective on the process of two-class classification.  In particular - as we will see here - the perceptron provides a simple geometric context for introducing the important concept of *regularization* (an idea we will see arise in various forms throughout the remainder of the text)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "ZU5-VKIcnnEJ",
    "outputId": "4be42d0d-bf07-4035-8aad-d59ae4d5d541"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: github-clone in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (1.2.0)\n",
      "Requirement already satisfied: requests>=2.20.0 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from github-clone) (2.32.3)\n",
      "Requirement already satisfied: docopt>=0.6.2 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from github-clone) (0.6.2)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from requests>=2.20.0->github-clone) (3.4.0)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from requests>=2.20.0->github-clone) (3.10)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from requests>=2.20.0->github-clone) (2.2.3)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from requests>=2.20.0->github-clone) (2024.12.14)\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m24.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.3.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
      "chapter_6_datasets already cloned!\n",
      "chapter_6_library already cloned!\n",
      "chapter_6_images already cloned!\n"
     ]
    }
   ],
   "source": [
    "# install github clone - allows for easy cloning of subdirectories\n",
    "!pip install github-clone\n",
    "from pathlib import Path \n",
    "\n",
    "# clone datasets\n",
    "if not Path('chapter_6_datasets').is_dir():\n",
    "    !ghclone https://github.com/neonwatty/machine-learning-refined-notes-assets/tree/main/notes/6_Linear_twoclass_classification/chapter_6_datasets\n",
    "else:\n",
    "    print('chapter_6_datasets already cloned!')\n",
    "\n",
    "# clone library subdirectory\n",
    "if not Path('chapter_6_library').is_dir():\n",
    "    !ghclone https://github.com/neonwatty/machine-learning-refined-notes-assets/tree/main/notes/6_Linear_twoclass_classification/chapter_6_library\n",
    "else:\n",
    "    print('chapter_6_library already cloned!')\n",
    "\n",
    "# clone images\n",
    "if not Path('chapter_6_images').is_dir():\n",
    "    !ghclone https://github.com/neonwatty/machine-learning-refined-notes-assets/tree/main/notes/6_Linear_twoclass_classification/chapter_6_images\n",
    "else:\n",
    "    print('chapter_6_images already cloned!')\n",
    "\n",
    "# append path for local library, data, and image import\n",
    "import sys\n",
    "sys.path.append('./chapter_6_library')\n",
    "sys.path.append('./chapter_6_datasets') \n",
    "sys.path.append('./chapter_6_images') \n",
    "\n",
    "# import section helper\n",
    "import section_6_4_helpers\n",
    "\n",
    "# dataset paths\n",
    "data_path_1 = 'chapter_6_datasets/2d_classification_data_v1.csv'\n",
    "\n",
    "# image paths\n",
    "image_path_1 = 'chapter_6_images/Fig_4_1.png'\n",
    "image_path_2 = 'chapter_6_images/Fig_4_2.png'\n",
    "image_path_3 = 'chapter_6_images/point_distance.png'\n",
    "image_path_4 = 'chapter_6_images/distance_to_boundary.png'\n",
    "\n",
    "# standard imports\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import Image, HTML\n",
    "\n",
    "# import autograd-wrapped numpy\n",
    "import autograd.numpy as np\n",
    "\n",
    "# this is needed to compensate for matplotlib notebook's tendancy to blow up images when plotted inline\n",
    "%matplotlib inline\n",
    "from matplotlib import rcParams\n",
    "rcParams['figure.autolayout'] = True\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "VNGMzHEjnnEK"
   },
   "source": [
    "## The Perceptron cost function"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yyd-XnMtnnEL"
   },
   "source": [
    "With two-class classification we have a training set of $P$ points $\\left\\{ \\left(\\mathbf{x}_{p},y_{p}\\right)\\right\\} _{p=1}^{P}$ - where $y_p$'s take on just two label values from $\\{-1, +1\\}$ - consisting of two classes which we would like to learn how to distinguish between automatically.  As we saw in our discussion of logistic regression, in the simplest instance our two classes of data are largely separated by a *linear decision boundary* with each class (largely) lying on either side.  This decision boundary, written as\n",
    "\n",
    "\\begin{equation}\n",
    "\\mathring{\\mathbf{x}}^{T}\\mathbf{w}^{\\,} = 0,\n",
    "\\end{equation}\n",
    "\n",
    "is a *point* when the dimension of the input is $N=1$ (as we saw in e.g., Example 2 of the previous Section), a *line* when $N = 2$ (as we saw in e.g, Example 3 of the previous Section), and is more generally for arbitray $N$ a *hyperplane* defined in the input space of a dataset.  This scenario can be best visualized in the case $N=2$, where we view the problem of classification 'from above' - showing the input of a dataset colored to denote class membership.  The default coloring scheme we use here - matching the scheme used in the previous Section - is to color points with label $y_p = -1$ blue and $y_p = +1$ red.  The linear decision boundary is here a line that best separates points from the $y_p = -1$ class from those of the $y_p = +1$ class, as shown figuratively in the panels below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 302
    },
    "id": "_nOs0rMTn-Ae",
    "outputId": "15066f2f-8dc3-467e-d24b-f58b05b2123d"
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 2,
     "metadata": {
      "image/png": {
       "width": 800
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(image_path_1, width=800)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "abZ-8mH7nnEL"
   },
   "source": [
    "<figure>\n",
    "  <figcaption>   \n",
    "<strong>Figure 1:</strong> <em> With the perceptron we aim to directly\n",
    " learn the linear decision boundary $\\mathring{\\mathbf{x}}^{T}\\mathbf{w}^{\\,} =0$ (shown\n",
    "here in black) to separate two classes of data, colored red (class $+1$) and blue (class $-1$), by dividing the input space into a red half-space where $\\mathring{\\mathbf{x}}^{T}\\mathbf{w}^{\\,} >0$,\n",
    "and a blue half-space where $\\mathring{\\mathbf{x}}^{T}\\mathbf{w}^{\\,} <0$. (left\n",
    "panel) A linearly separable dataset where it is possible to learn\n",
    "a hyperplane to perfectly separate the two classes. (right panel)\n",
    "A dataset with two overlapping classes. Although the distribution\n",
    "of data does not allow for perfect linear separation, the perceptron still aims to find\n",
    "a hyperplane that minimizes the number of misclassified points\n",
    "that end up in the wrong half-space.</em>  </figcaption> \n",
    "</figure>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ndp-uQdbnnEM"
   },
   "source": [
    "A linear decision boundary cuts the input space into two *half-spaces*, one lying 'above' the hyperplane where $\\mathring{\\mathbf{x}}^{T}\\mathbf{w}^{\\,} > 0$ and one lying 'below' it where $\\mathring{\\mathbf{x}}^{T}\\mathbf{w}^{\\,}  < 0$.  Notice then, as depicted visually in the figure above, that a proper set of weights $\\mathbf{w}$ define a linear decision boundary that separates a two-class dataset as well as possible with *as many members of one class as possible lying above it, and likewise as many members as possible of the other class lying below it*.  Because we can always flip the orientation of an ideal hyperplane by multiplying it by $-1$ (or likewise because we can always swap our two label values) we can say more specifically that when the weights of a hyperplane are tuned properly members of the class $y_p = +1$ lie (mostly)'above' it, while members of the $y_p = -1$ class lie (mostly) 'below' it.  In other words, our *desired* set of weights define a hyperplane where as often as possible we have that\n",
    "\n",
    "\\begin{equation}\n",
    "\\begin{array}\n",
    "\\\n",
    "\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{\\,} >0 & \\,\\,\\,\\,\\text{if} \\,\\,\\, y_{p}=+1\\\\\n",
    "\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{\\,} <0 & \\,\\,\\,\\,\\text{if} \\,\\,\\, y_{p}=-1.\n",
    "\\end{array}\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "UgcBmIkonnEM"
   },
   "source": [
    "Because of our choice of label values we can consolidate the ideal conditions above into the single equation below\n",
    "\n",
    "\\begin{equation}\n",
    "-\\overset{\\,}{y}_{p}\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{\\,} <0.\n",
    "\\end{equation}\n",
    "\n",
    "Again we can do so specifically because we chose the label values $y_p \\in \\{-1,+1\\}$.  Likewise by taking the maximum of this quantity and zero we can then write this ideal condition, which states that a hyperplane correctly classifies the point $\\mathbf{x}_{p}$, equivalently forming a *point-wise cost*\n",
    "\n",
    "\\begin{equation}\n",
    "g_p\\left(\\mathbf{w}\\right) = \\text{max}\\left(0,\\,-\\overset{\\,}{y}_{p}\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{\\,}\\right)=0\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "67oJSuxAnnEN"
   },
   "source": [
    "Note that the expression $\\text{max}\\left(0,-\\overset{\\,}{y}_{p}\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{\\,}\\right)$ is always nonnegative, since it returns zero if $\\mathbf{x}_{p}$ is classified correctly, and returns a *positive value* if the\n",
    "point is classified incorrectly.  The functional form of this point-wise cost $\\text{max}\\left(0,\\cdot\\right)$ is called a *rectified linear unit* (see the Appendix of this text for a historical explination of this term).  Because these point-wise costs are nonnegative and equal *zero* when our weights are tuned correctly, we can take their average over the entire dataset to form a proper cost function as"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xvfDltxKnnEN"
   },
   "source": [
    "\\begin{equation}\n",
    "g\\left(\\mathbf{w}\\right)=  \\frac{1}{P}\\sum_{p=1}^Pg_p\\left(\\mathbf{w}\\right) = \\frac{1}{P}\\sum_{p=1}^P\\text{max}\\left(0,-\\overset{\\,}{y}_{p}\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{\\,}\\right).\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TJ2AcxzSnnEN"
   },
   "source": [
    "When minimized appropriately this cost function can be used to recover the ideal weights satisfying equations (3) - (5) as often as possible. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MlPzm2tfnnEN"
   },
   "source": [
    "This cost function goes by many names such as the *perceptron* cost, the *rectified linear unit* cost (or *ReLU cost* for short), and the *hinge cost* (since when plotted a ReLU function looks like a hinge). This cost function is *always convex* but has only a single (discontinuous) derivative in each input dimension. This implies that we can only use zero and first order local optimization schemes (i.e., not Newton's method).  Note that the perceptron cost *always* has a trivial solution at  $\\mathbf{w} = \\mathbf{0}$, since indeed $g\\left(\\mathbf{0}\\right) = 0$, thus one may need to take care in practice to avoid finding it (or a point too close to it) accidentally."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bqea148gnnEN"
   },
   "source": [
    "##  The smooth softmax approximation to the ReLU cost"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Zfs6Bu8PnnEO"
   },
   "source": [
    "Learning and optimization go hand in hand, and as we know from the discussion above the ReLU function limits the number of optimization tools we can bring to bear for learning. It not only prohibits the use of Newton's method but forces us to be very careful about how we choose our steplength parameter $\\alpha$ with gradient descent as well (as detailed in the example above). Here we describe a common approach to ameliorating this issue by introducing a smooth approximation to this cost function. This practical idea takes many forms depending on the cost function at play, but the general idea is this: when dealing with a cost function that has some deficit (insofar as local optimization is concerned) replace it with a smooth (or at least twice differentiable) cost function that closely matches it everywhere. If the approximation closely matches the true cost function then for the small amount of accuracy (we will after all be minimizing the approximation, not the true function itself) we significantly broaden the set of optimization tools we can use."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "u5F05xmunnEO"
   },
   "source": [
    "One popular way of doing this for the ReLU cost function is via the *softmax* function defined as\n",
    "\n",
    "\\begin{equation}\n",
    "\\text{soft}\\left(s_0,s_1,...,s_{C-1}\\right) = \\text{log}\\left(e^{s_0} + e^{s_1} + \\cdots + e^{s_{C-1}} \\right)\n",
    "\\end{equation}\n",
    "\n",
    "where $s_0,\\,s_1,\\,...,s_{C-1}$ are any $C$ scalar vaules - which is a generic smooth approximation to the *max* function, i.e., \n",
    "\n",
    "\\begin{equation}\n",
    "\\text{soft}\\left(s_0,s_1,...,s_{C-1}\\right) \\approx \\text{max}\\left(s_0,s_1,...,s_{C-1}\\right)\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jfNYoRKFnnEO"
   },
   "source": [
    "To see why the softmax approximates the max function let us look at the simple case when $C = 2$. \n",
    "\n",
    "Suppose momentarily that $s_{0}\\leq s_{1}$, so that $\\mbox{max}\\left(s_{0},\\,s_{1}\\right)=s_{1}$.  Therefore $\\mbox{max}\\left(s_{0},\\,s_{1}\\right)$ can be written as $\\mbox{max}\\left(s_{0},\\,s_{1}\\right)=s_{0}+\\left(s_{1}-s_{0}\\right)$,\n",
    "or equivalently as $\\mbox{max}\\left(s_{0},\\,s_{1}\\right)=\\mbox{log}\\left(e^{s_{0}}\\right)+\\mbox{log}\\left(e^{s_{1}-s_{0}}\\right)$. Written in this\n",
    "way we can see that $\\mbox{log}\\left(e^{s_{0}}\\right)+\\mbox{log}\\left(1+e^{s_{1} s_{0}}\\right)=\\mbox{log}\\left(e^{s_{0}}+e^{s_{1}}\\right)=\\mbox{soft}\\left(s_{0},s_{1}\\right)$ is always larger than $\\mbox{max}\\left(s_{0},\\,s_{1}\\right)$ but not by much, especially when $e^{s_{1}-s_{0}}\\gg1$. Since the same argument can be made if $s_{0}\\geq s_{1}$ we can say generally that\n",
    "$ $$\\mbox{soft}\\left(s_{0},s_{1}\\right)\\approx\\mbox{max}\\left(s_{0},s_{1}\\right)$.  The more general case follows similarly as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 244
    },
    "id": "LvIHwWUcoE2B",
    "outputId": "be8acd23-28d3-4bd0-f4b7-895ea67d4879"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 3,
     "metadata": {
      "image/png": {
       "width": 400
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(image_path_2, width=400)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ALAdKX55nnEO"
   },
   "source": [
    "<figure>\n",
    "  <figcaption>   \n",
    "<strong>Figure 2:</strong> <em> \n",
    "    Plots of the ReLU\n",
    "perceptron $g\\left(s\\right)=\\mbox{max}\\left(0,\\,s\\right)$\n",
    "(shown in green) as well as its smooth softmax approximation $g\\left(s\\right)=\\mbox{soft}\\left(0,\\,s\\right)=\\mbox{log}\\left(1+e^{s}\\right)$\n",
    "(shown in dashed black).\n",
    "    </em>  </figcaption> \n",
    "</figure>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "8QL4DFbLnnEO"
   },
   "source": [
    "Returning to the ReLU perceptron cost function in equation (5), we replace the $p^{th}$ summand with its softmax approximation, making this our point-wise cost\n",
    "\n",
    "\\begin{equation}\n",
    "g_p\\left(\\mathbf{w}\\right) = \\text{soft}\\left(0,-\\overset{\\,}{y}_{p}\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{\\,}\\right)= \\text{log}\\left(e^{0} + e^{-\\overset{\\,}{y}_{p}\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{\\,}}\\right) = \\text{log}\\left(1 + e^{-\\overset{\\,}{y}_{p}\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{\\,}}\\right)\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "pVlmyftOnnEP"
   },
   "source": [
    "giving the overall cost function as "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "9rC9OXD0nnEP"
   },
   "source": [
    "\\begin{equation}\n",
    "g\\left(\\mathbf{w}\\right)=\\sum_{p=1}^P g_p\\left(\\mathbf{w}\\right) = \\underset{p=1}{\\overset{P}{\\sum}}\\text{log}\\left(1 + e^{-\\overset{\\,}{y}_{p}\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{\\,}}\\right)\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "7BttVYFInnEP"
   },
   "source": [
    "which is the *Softmax cost* we saw previously derived from the logistic regression perspective on two-class classification in the previous Section.  This is why the cost is called *Softmax*, since it derives from the general softmax approximation to the max function.\n",
    "\n",
    "Note that *like* the ReLU cost - as we already know - the Softmax cost is convex. However *unlike* the ReLU cost, the softmax has infinitely many derivatives and Newton's method can therefore be used to minimize it. Moreover, softmax does not have a trivial solution at zero like the ReLU cost does.  Nonetheless, the fact that the Softmax cost so closely approximates the ReLU shows just how closely aligned - in the end - both logistic regression and the perceptron truly are. Practically speaking their differences lie in how well - for a particular dataset - one can optimize either one, along with (what is very often slight) differences in the quality of each cost function's learned decision boundary.  Of course when the Softmax is employed from the perceptron perspective there is no qualitative difference between the perceptron and logistic regression at all."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "k_Jv8pHrnnEP"
   },
   "source": [
    "## A technical problem with linearly separable datasets "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "awPOxWOennEP"
   },
   "source": [
    "Imagine that we have a dataset whose two classes can be perfectly separated by a hyperplane, and that we have chosen an appropriate cost function to minimize it in order to determine proper weights for our model.  Imagine further that we are *extremely lucky* and  our *initialization* $\\mathbf{w}^0$ produces a linear decision boundary $\\mathring{\\mathbf{x}}_{\\,}^T\\mathbf{w}^{0} = 0$  with *perfect sepearation*.  This means that - according to equation (4) - that for each of our $P$ points we have that  \n",
    "\n",
    "\\begin{equation}\n",
    "-\\overset{\\,}{y}_{p}\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{0} <0\n",
    "\\end{equation}\n",
    "\n",
    "and likewise that the point-wise RelLU cost in equation (5) is zero for every point i.e., $g_p\\left(\\mathbf{w}^0\\right) = \\text{max}\\left(0,\\,-\\overset{\\,}{y}_{p}\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{0}\\right)=0$ and so the ReLU cost is *exactly equal to zero*\n",
    "\n",
    "\\begin{equation}\n",
    "g\\left(\\mathbf{w}^0\\right) = \\frac{1}{P}\\sum_{p=1}^P\\text{max}\\left(0,-\\overset{\\,}{y}_{p}\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{0}\\right) = 0.\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5rfoTpjBnnEP"
   },
   "source": [
    "Since the ReLU cost value is already zero, its lowest value, this means that we would *halt our local optimization immediately*.  For example, since the gradient of this cost is also zero at $\\mathbf{w}^0$ (see Example 1 above where the form of this gradient was given) a gradient descent step would not move us from $\\mathbf{w}^0$.  However this will *not* happen if we instead employed the Softmax cost."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "nV-2YjHznnEP"
   },
   "source": [
    "Since the quantity $-\\overset{\\,}{y}_{p}\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{0} <0$ its *negative exponential* is *larger than zero* i.e., $e^{-\\overset{\\,}{y}_{p}\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{0}} > 0$, which means that the softmax point-wise cost is also nonnegative $g_p\\left(\\mathbf{w}^0\\right) = \\text{log}\\left(1 + e^{-\\overset{\\,}{y}_{p}\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{0}}\\right) > 0$ and hence too the Softmax cost is nonnegative as well \n",
    "\n",
    "\\begin{equation}\n",
    "g\\left(\\mathbf{w}^0\\right)= \\sum_{p=1}^P\\text{log}\\left(1 + e^{-\\overset{\\,}{y}_{p}\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{0}}\\right) > 0.\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "E74AHIuZnnEQ"
   },
   "source": [
    "This means that we in applying any local optimization scheme like e.g., gradient descent we will *indeed* take steps away from $\\mathbf{w}^0$ in order to drive the value of the Softmax cost lower and lower towards its minimum at zero.  In fact - with data that is indeed linearly separable - the Softmax cost achieves this lower bound *only when the magnitude of the weights grows to infinity*.  This is clear from the fact each individual term $\\text{log}\\left(1 + e^{-C}\\right) = 0$ only as $C \\longrightarrow \\infty$.  Indeed if we *multiply our initialization $\\mathbf{w}^0$* by any constant $C > 1$ we can *decrease* the value of any negative exponential involving one of our data points since $e^{-C} < 1$ and so\n",
    "\n",
    "\\begin{equation}\n",
    "e^{-\\overset{\\,}{y}_{p}\\mathring{\\mathbf{x}}_{p}^TC\\mathbf{w}^{0}} = e^{-C}e^{-\\overset{\\,}{y}_{p}\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{0}} < e^{-\\overset{\\,}{y}_{p}\\mathring{\\mathbf{x}}_{p}^T\\mathbf{w}^{0}}.\n",
    "\\end{equation}\n",
    "\n",
    "This likewise decreases the Softmax cost as well with the minimum achieved only as $C \\longrightarrow \\infty$.  Note however that regardless of the scalar $C > 1$ value involved the *decision boundary defined by the initial weights $\\mathring{\\mathbf{x}}_{\\,}^T\\mathbf{w}^{0} = 0$ does not change location, since we still have that $C\\,\\mathring{\\mathbf{x}}_{\\,}^T\\mathbf{w}^{0} = 0$* (indeed this is true for any non-zero scalar $C$).  So even though the location of the separating hyperplane need not change, with the Softmax cost we still take more and more steps in minimization since (in the case of linearly separable data) its minimum lies off at infinity.  This can cause severe numerical instability issues with local optimizaiton schemes that make *large progress* at each step - particularly Newton's method - since they will tend to rapidly diverge to infinity."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "mL7wGpMvnnEQ"
   },
   "source": [
    "Notice: because the Softmax and Cross-Entropy costs are equivalent (as discussed in the previous Section), this issue equally presents itself when using the Cross-Entropy cost as well."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "F_ETRT61nnEQ"
   },
   "source": [
    "#### <span style=\"color:#a50e3e;\">Example 2: </span> Using Newton's method to minimize the Softmax cost"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "LHZTSziKnnEQ"
   },
   "source": [
    "In applying Newton's method to minimize the Softmax over linearly separable data it is easily possible to run into numerical instability issues as the global minimum of the cost technically lies at infinity.  Here we examine a simple instance of this behavior using the single input dataset shown in the previous Section.  In this example we illustrate the progress of 5 Newton steps beginning at the point $\\mathbf{w} = \\begin{bmatrix} 1 \\\\ 1 \\end{bmatrix}$.  Within 5 steps we have reached a point providing a very good fit to the data (here we plot the $\\text{tanh}\\left(\\cdot\\right)$ fit using the logistic regressoion perspective on the Softmax cost), and one that is already quite large in magnitude (as can be seen in the right panel below).  We can see here by the trajectory of the steps, which are traveling linearly towards the mininum out at $\\begin{bmatrix} -\\infty \\\\ \\infty \\end{bmatrix}$, that the location of the linear decision boundary (here a point) is not changing after the first step or two. In other words, after the first few steps we each subsequent step is simply multiplying its predecessor by a scalar value $C > 1$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 299
    },
    "id": "msMPnvzVnnEQ",
    "outputId": "2b054b92-bf17-46ea-da6f-0115df0702a0"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### define softmax cost ###\n",
    "# compute linear combination of input point\n",
    "def model(x,w):\n",
    "    a = w[0] + np.dot(x.T,w[1:])\n",
    "    return a.T\n",
    "\n",
    "# the convex softmax cost function\n",
    "def softmax(w):\n",
    "    cost = np.sum(np.log(1 + np.exp(-y*model(x,w))))\n",
    "    return cost/float(np.size(y))\n",
    "\n",
    "# load in dataset\n",
    "data = np.loadtxt(data_path_1, delimiter = ',')\n",
    "\n",
    "# get input/output pairs\n",
    "x = data[:-1,:]\n",
    "y = data[-1:,:] \n",
    "\n",
    "# run gradient descent to minimize the softmax cost\n",
    "g = softmax; w = np.ones((2,1)); max_its = 5;\n",
    "weight_history,cost_history = section_6_4_helpers.newtons_method(g,max_its,w,epsilon = 10**(-7))\n",
    "\n",
    "# create a static figure illustrating gradient descent steps \n",
    "animator = section_6_4_helpers.classification_2d_visualizer(data,g)\n",
    "animator.static_fig(weight_history,num_contours = 25,viewmax = 25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "HsiTxZBpnnER"
   },
   "source": [
    "Notice that if we simply flip one of the labels - making this dataset not perfectly linearly separable - the corresponding cost function does not have a global minimum out at infinity, as illustrated in the contour plot below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 225
    },
    "id": "oEyPPJ7ynnER",
    "outputId": "0d41fc2d-3262-4eb5-ceae-51b2db90e653"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# switch a label\n",
    "y[0,-1] = -1\n",
    "data = np.vstack((x,y))\n",
    "\n",
    "# draw contour of this new data\n",
    "animator = section_6_4_helpers.classification_2d_visualizer(data,softmax)\n",
    "\n",
    "# create a static figure illustrating gradient descent steps \n",
    "animator.static_fig([],num_contours = 15,viewmax = 25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "FMTsQJlCnnER"
   },
   "source": [
    " ##  Regularization and two-class classification"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_Z7KpXWtnnES"
   },
   "source": [
    "How can we prevent this potential problem when employing the Softmax or Cross-Entropy cost?  One approach can be to employ our local optimization schemes more carefully by eg., taking fewer steps and / or halting a scheme if the magnitude of the weights grows larger than a large pre-defined constant (this is called *early-stopping*).  Another approach is to *control the magnitude of the weights during the optimization procedure itself*.  Both approaches are generally referred to in the jargon of machine learning as *regularization strategies*.  The former strategy is straightfoward, requiring slight adjustments to the way we have typically employed local optimization, but the latter approach requires some further explanation which we now provide. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "0warIdginnES"
   },
   "source": [
    "To control the magnitude of $\\mathbf{w}$ means that we want to control the size of the $N+1$ individual weights it contains\n",
    "\n",
    "\\begin{equation}\n",
    "\\mathbf{w} = \n",
    "\\begin{bmatrix}\n",
    "w_0 \\\\\n",
    "w_1 \\\\\n",
    "\\vdots \\\\\n",
    "w_N\n",
    "\\end{bmatrix}.\n",
    "\\end{equation}\n",
    "\n",
    "We can do this by *directly* controling the size of just $N$ of these weights, and it is particularly convenient to do so using the final $N$ feature touching weights $w_1,\\,w_2,\\,...,w_N$ because these define the *normal vector* to the linear decision boundary $\\mathring{\\mathbf{x}}_{\\,}^T\\mathbf{w}^{\\,} = 0$.  To more easily introduce the geometric concepts that follow we will use our bias / feature weight notation for $\\mathbf{w}$ first introduced in [Section 5.2](https://jermwatt.github.io/machine_learning_refined/notes/5_Linear_regression/5_2_Least.html).  This provides us with individual notation for the bias and feature-touching weights as\n",
    "\n",
    "\\begin{equation}\n",
    "\\text{(bias):}\\,\\, b = w_0 \\,\\,\\,\\,\\,\\,\\,\\, \\text{(feature-touching weights):} \\,\\,\\,\\,\\,\\, \\boldsymbol{\\omega} = \n",
    "\\begin{bmatrix}\n",
    "w_1 \\\\\n",
    "w_2 \\\\ \n",
    "\\vdots \\\\\n",
    "w_N\n",
    "\\end{bmatrix}.\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "8T4ZUlMXnnES"
   },
   "source": [
    "With this notation we can express a linear decision boundary as\n",
    "\n",
    "\\begin{equation}\n",
    "\\mathring{\\mathbf{x}}_{\\,}^T \\mathbf{w} = b + \\overset{\\,}{\\mathbf{x}}_{\\,}^T\\boldsymbol{\\omega} = 0.\n",
    "\\end{equation}\n",
    "\n",
    "To begin to see why this notation is useful first note how - geometrically speaking - the feature-touching weights $\\boldsymbol{\\omega}$ define the *normal vector of the linear decision boundary*.  The *normal* vector to a hyperplane (like our decision boundary) is always *perpindicular* to it - as illustrated in the Figure below.  We can *always compute the error - also called the *signed* distance - of a point $\\mathbf{x}_p$ to a linear decision boundary in terms of the normal vector $\\boldsymbol{\\omega}$*.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 323
    },
    "id": "uSODy2HFoO2g",
    "outputId": "17941ebc-68db-4647-9eb6-17573c346f72"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 6,
     "metadata": {
      "image/png": {
       "width": 500
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(image_path_3, width=500)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ehJ61b8QnnET"
   },
   "source": [
    "<figure>\n",
    "  <figcaption>   \n",
    "<strong>Figure 3:</strong> <em> \n",
    "A linear decision boundary written as $ b + \\overset{\\,}{\\mathbf{x}}_{\\,}^T\\boldsymbol{\\omega} = 0$ has a normal vector $\\boldsymbol{\\omega}$ defined by its feature-touching weights.  To compute the signed distance of a point $\\mathbf{x}_p$ to the boundary we mark the translation of the decision boundary passing through this point as $ b + \\overset{\\,}{\\mathbf{x}}_{\\,}^T\\boldsymbol{\\omega} = \\beta$, and the projection of the point onto the decision boundary as $\\mathbf{x}_p^{\\prime}$.\n",
    "    </em>  </figcaption> \n",
    "</figure>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "LQnzktZ8nnET"
   },
   "source": [
    "To see how this is possible, imagine we have a point $\\mathbf{x}_p$ lying 'above' the linear decision boundary on a translate of the decision boundary where  $b + \\overset{\\,}{\\mathbf{x}}_{\\,}^T\\boldsymbol{\\omega} = \\beta > 0$, as illustrated in the Figure above.  The same simple argument that follows can be made if $\\mathbf{x}_p$ lies 'below' it as well.  To compute the distance of $\\mathbf{x}_p$ to the decision boundary imagine we know the location of its *vertical projection* onto the decision boundary which will call $\\mathbf{x}_p^{\\prime}$.  To compute our desired error we want to compute the signed distance between $\\mathbf{x}_p$ and its vertical projection, i.e., the length of the vector $\\mathbf{x}_p^{\\prime} -  \\mathbf{x}_p$ times the sign of $\\beta$ which here is $+1$ since we assume the point lies above the decision boundary hence $\\beta > 0$, i.e., $d = \\left\\Vert \\mathbf{x}_p^{\\prime} -  \\mathbf{x}_p \\right\\Vert_2 \\text{sign}\\left(\\beta\\right) = \\left\\Vert \\mathbf{x}_p^{\\prime} -  \\mathbf{x}_p \\right\\Vert_2$.  Now, because *this vector is also perpindicular* to the decision boundary (and so is *paralell* to the normal vector $\\boldsymbol{\\omega}$)  the *inner-product rule* gives\n",
    "\n",
    "\\begin{equation}\n",
    "\\left(\\mathbf{x}_p^{\\prime} -  \\mathbf{x}_p\\right)^T\\boldsymbol{\\omega} = \\left\\Vert \\mathbf{x}_p^{\\prime} -  \\mathbf{x}_p \\right\\Vert_2 \\left\\Vert \\overset{\\,}{\\boldsymbol{\\omega}} \\right\\Vert_2 = d\\,\\left\\Vert \\overset{\\,}{\\boldsymbol{\\omega}} \\right\\Vert_2 \n",
    "\\end{equation}\n",
    "\n",
    "Now if we take the difference between our decision boundary and its translation evaluated at $\\mathbf{x}_p^{\\prime}$ and $\\mathbf{x}_p$ respectively, we have simplifying\n",
    "\n",
    "\\begin{equation}\n",
    "\\beta - 0 = \\left(b + \\left(\\overset{\\,}{\\mathbf{x}}_{p}^{\\prime}\\right)^T \\boldsymbol{\\omega}\\right)- \\left(b + \\overset{\\,}{\\mathbf{x}}_{p}^T \\boldsymbol{\\omega}\\right) = \\left(\\mathbf{x}_p^{\\prime} -  \\mathbf{x}_p\\right)^T\\boldsymbol{\\omega}\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "3-1KD1cynnET"
   },
   "source": [
    "Since both formulae are equal to $\\left(\\mathbf{x}_p^{\\prime} -  \\mathbf{x}_p\\right)^T\\boldsymbol{\\omega}$ we can set them equal to each other, which gives\n",
    "\n",
    "\\begin{equation}\n",
    "d\\,\\left\\Vert \\overset{\\,}{\\boldsymbol{\\omega}} \\right\\Vert_2 = \\beta\n",
    "\\end{equation}\n",
    "\n",
    "or in other words that the signed distance $d$ of $\\mathbf{x}_p$ to the decision boundary is \n",
    "\n",
    "\\begin{equation}\n",
    "d = \\frac{\\beta}{\\left\\Vert \\overset{\\,}{\\boldsymbol{\\omega}} \\right\\Vert_2 } = \\frac{b + \\overset{\\,}{\\mathbf{x}}_{p}^T\\boldsymbol{\\omega} }{\\left\\Vert \\overset{\\,}{\\boldsymbol{\\omega}} \\right\\Vert_2 }.\n",
    "\\end{equation}\n",
    "\n",
    "Note that we need not worry dividing by zero here since if the feature-touching weights $\\boldsymbol{\\omega}$ were all zero, this would imply that the bias $b = 0$ as well and we have no decision boundary at all.  Also notice, this analysis implies that if the feature-touching weights have *unit length* as $\\left\\Vert \\boldsymbol{\\omega}\\right\\Vert_2 = 1$ then the signed distance $d$ of a point $\\mathbf{x}_p$ to the decision boundary is given *simply by its evaluation* $b + \\mathbf{x}_p^T \\boldsymbol{\\omega}$.  Finally note that if $\\mathbf{x}_p$ were to lie below the decision boundary and $\\beta < 0$ nothing about the final formulae derived above will change."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "id": "7v4ZwoGZnnET"
   },
   "source": [
    "We mark this point-to-decision-boundary distance on points in the figure below, here the input dimension $N = 3$ and the decision boundary is a true hyperplane."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "uh1A3xe-nnET",
    "outputId": "065e4467-5b2d-4691-f323-c458ef3f1171"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img src=\"chapter_6_images/distance_to_boundary.png\" width=\"60%\" height=\"auto\" alt=\"\"/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import HTML\n",
    "HTML('''<img src=\"''' + image_path_4 + '''\" width=\"60%\" height=\"auto\" alt=\"\"/>''')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 343
    },
    "id": "OqhdgwXLoWUn",
    "outputId": "7a07e410-bf07-4291-e8b8-2d1664c5440c"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 11,
     "metadata": {
      "image/png": {
       "width": 600
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(image_path_4, width=600)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "FQxTQaQnnnET"
   },
   "source": [
    "<figure>\n",
    "  <figcaption>   \n",
    "<strong>Figure 4:</strong> <em> Visual representation of the distance to the hyperplane $b+\\mathbf{x}^T\\boldsymbol{\\omega}$, of two points $\\mathbf{x}_p$ and $\\mathbf{x}_q$ lying above it. </em>  </figcaption> \n",
    "</figure>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "UGZxIgzInnET"
   },
   "source": [
    "Remember, as detailed above, we can scale any linear decision boundary by a non-zero scalar $C$ and it still defines the same hyperplane.  So if - in particular - we multiply by $C = \\frac{1}{\\left\\Vert \\overset{\\,}{\\boldsymbol{\\omega}} \\right\\Vert_2}$ we have\n",
    "\n",
    "\\begin{equation}\n",
    " \\frac{b + \\overset{\\,}{\\mathbf{x}}_{\\,}^T\\boldsymbol{\\omega} }{\\left\\Vert \\overset{\\,}{\\boldsymbol{\\omega}} \\right\\Vert_2 } = \\frac{b}{\\left\\Vert \\overset{\\,}{\\boldsymbol{\\omega}} \\right\\Vert_2} + \\overset{\\,}{\\mathbf{x}}_{\\,}^T\\frac{\\boldsymbol{\\omega}}{\\left\\Vert \\overset{\\,}{\\boldsymbol{\\omega}} \\right\\Vert_2} = 0\n",
    "\\end{equation}\n",
    "\n",
    "we do not change the nature of our decision boundary and now our feature-touching weights have unit length as $\\left\\Vert \\frac{\\boldsymbol{\\omega}}{\\left\\Vert \\overset{\\,}{\\boldsymbol{\\omega}} \\right\\Vert_2}\\right \\Vert_2 = 1$.  In other words, *regardless of how large our weights $\\mathbf{w}$ were to begin with we can always normalize them in a consistent way by dividing off the magnitude of $\\boldsymbol{\\omega}$*.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "KkD17YgmnnEU"
   },
   "source": [
    "This normalization scheme is particularly useful in the context of the technical issue with the Softmax / Cross-entropy highlighted in the previous Subsection. because clearly a decision boundary that perfectly separates two classes of data *can be feature-weight normalized* to prevent its weights from growing too large (and diverging too infinity).  Of coures we do not want to wait to perform this normaliation until *after* we run our local optimization, since this will not prevent the magnitude of the weights from potentially diverging, but *during* optimization.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "v-HQ32nrnnEU"
   },
   "source": [
    "With can achieve this by *constraining* the Softmax / Cross-Entropy cost so that feature-touching weights always have length one i.e., $\\left\\Vert \\boldsymbol{\\omega} \\right\\Vert_2 = 1$.  Formally we can phrase this minimization (employing the Softmax cost) to as a *constrained* optimization problem as follows"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "OXws_adVnnEU"
   },
   "source": [
    "\\begin{equation}\n",
    "\\begin{aligned}\n",
    "\\underset{b, \\,\\boldsymbol{\\omega}_{\\,}}{\\,\\,\\,\\,\\,\\mbox{minimize}\\,\\,\\,} & \\,\\,\\,\\, \\frac{1}{P}\\sum_{p=1}^P\\text{log}\\left(1 + e^{-y_p\\left(b + \\mathbf{x}_p^T \\boldsymbol{\\omega}^{\\,}_{\\,}\\right)}\\right) \\\\\n",
    "\\mbox{subject to}\\,\\,\\, & \\,\\,\\,\\,\\, \\left \\Vert \\boldsymbol{\\omega} \\right \\Vert_2^2 = 1\n",
    "\\end{aligned}\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hiaxw4ARnnEU"
   },
   "source": [
    "By solving this *constrained* version of the Softmax cost we can still learn a decision boundary that perfectly separates two classes of data, but we avoid divergence in the magnitude of the weights by keeping their magnitude *feature-weight normalized*.\n",
    "\n",
    "This formulation can indeed be solved by simple extensions of the local optimization methods detailed in Chapters 2 -4 (see this Chapter's exercises for further details).\n",
    "However a more popular approach in the machine learning community is to 'relax' this constrinaed formulation and instead solve the highly related *unconstrained problem*.  This relaxed form of the problem consists in minimizing a cost functionn that is a linear combination of our original Softmax cost the magnitude of the feature weights "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_rw34EngnnEU"
   },
   "source": [
    "\\begin{equation}\n",
    "g\\left(b,\\boldsymbol{\\omega}\\right) = \\frac{1}{P}\\sum_{p=1}^P\\text{log}\\left(1 + e^{-y_p\\left(b + \\mathbf{x}_p^T \\boldsymbol{\\omega}^{\\,}_{\\,}\\right)}\\right) + \\lambda\\, \\left \\Vert \\boldsymbol{\\omega} \\right \\Vert_2^2 \n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Rp-QycRennEU"
   },
   "source": [
    "which we can minimize using any of our familiar local optimization schemes.  Note here the *regularization parameter* $\\lambda \\geq 0$.  Here in adding the magnitude of the feature-touching weights to our Softmax cost we 'put pressure' on both terms, and aim to make both small.  The parameter $\\lambda$ is used to balance how strongly we pressure one term or the other.  In minimizing the first term, our Softmax cost, we are still looking to learn an excellent linear decision boundary.  In also minimizing the second term, the magnitude of the feature-touching weights $\\lambda\\, \\left \\Vert \\boldsymbol{\\omega} \\right \\Vert_2^2$ also called a *regularizer* - we incentivize the learning of *small* weights.  This prevents the divergence of their magnitude since if their size does start to grow we our entire cost function 'suffers' because of it, and becomes large.  Because of this the value of $\\lambda$ is typically chosen to be small (and positive) in practice, although some fine-tuning can be useful.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "id": "6L1AGzajnnEU"
   },
   "source": [
    "#### <span style=\"color:#a50e3e;\">Example 3: </span> Using Newton's method to minimize a regularized Softmax cost"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "cOtAu9-OnnEU"
   },
   "source": [
    "Here we repeat the experiment of the previous Example, but add a regularizer with $\\lambda = 10^(-3)$ to the Softmax cost.  In the right panel below we show the contour plot of the regularized cost function, and we can see its global minimum no longer lies at infinity.  However we still learn a perfect decision boundary as illustrated in the left panel by a tightly fitting $\\text{tanh}\\left(\\cdot\\right)$ function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 299
    },
    "id": "MD1Z60GWnnEV",
    "outputId": "9c7ed490-2990-44c4-ce6d-4e088b558418"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.9/dist-packages/autograd/tracer.py:48: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.\n",
      "To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.\n",
      "  return f_raw(*args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### define softmax cost ###\n",
    "# compute linear combination of input point\n",
    "def model(x,w):\n",
    "    a = w[0] + np.dot(x.T,w[1:])\n",
    "    return a.T\n",
    "\n",
    "# the convex softmax cost function\n",
    "lam = 2*10**(-3)\n",
    "def softmax(w):\n",
    "    # compute cost value\n",
    "    cost = np.sum(np.log(1 + np.exp(-y*model(x,w))))\n",
    "    \n",
    "    # add regularizer\n",
    "    cost += lam*np.sum(w[1:]**2)\n",
    "    return cost/float(np.size(y))\n",
    "\n",
    "# load in dataset\n",
    "data = np.loadtxt(data_path_1, delimiter = ',')\n",
    "\n",
    "# get input/output pairs\n",
    "x = data[:-1,:]\n",
    "y = data[-1:,:] \n",
    "\n",
    "# run gradient descent to minimize the softmax cost\n",
    "g = softmax; w = np.ones((2,1)); max_its = 5;\n",
    "weight_history,cost_history = section_6_4_helpers.newtons_method(g,max_its,w,epsilon = 10**(-7))\n",
    "\n",
    "# create instance of logisic regression demo and load in data, cost function, and descent history\n",
    "animator = section_6_4_helpers.classification_2d_visualizer(data,softmax)\n",
    "\n",
    "# create a static figure illustrating gradient descent steps \n",
    "animator.static_fig(weight_history,num_contours = 25,viewmax = 100)"
   ]
  }
 ],
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